Identification of genomic aberrations in hemangioblastoma by droplet digital PCR and SNP microarray highlights novel candidate genes and pathways for pathogenesis

Abstract

BackgroundThe genetic mechanisms underlying hemangioblastoma development are still largely unknown. We used high-resolution single nucleotide polymorphism microarrays and droplet digital PCR analysis to detect copy number variations (CNVs) in total of 45 hemangioblastoma tumors.ResultsWe identified 94 CNVs with a median of 18 CNVs per sample. The most frequently gained regions were on chromosomes 1 (p36.32) and 7 (p11.2). These regions contain the EGFR and PRDM16 genes. Recurrent losses were located at chromosome 12 (q24.13), which includes the gene PTPN11.ConclusionsOur findings provide the first high-resolution genome-wide view of chromosomal changes in hemangioblastoma and identify 23 candidate genes: EGFR, PRDM16, PTPN11, HOXD11, HOXD13, FLT3, PTCH, FGFR1, FOXP1, GPC3, HOXC13, HOXC11, MKL1, CHEK2, IRF4, GPHN, IKZF1, RB1, HOXA9, and micro RNA, such as hsa-mir-196a-2 for hemangioblastoma pathogenesis. Furthermore, our data implicate that cell proliferation and angiogenesis promoting pathways may be involved in the molecular pathogenesis of hemangioblastoma.

MicroRNA-152 inhibits ovarian cancer cell proliferation and migration and may infer improved outcomes in ovarian cancer through targeting FOXP1

“…FOXP1 expression has been reported to be closely associated with the degree of malignancy of EOC and may be a reliable index for the prognosis of OC (16). Function and bioinformatics analyses have revealed that FOXP1 was negatively related with miR-152 (17). Therefore, the present study aimed to reveal the mechanism between miR-152 and FOXP1.…”

Identifying the spatial and temporal dynamics of molecularly-distinct glioblastoma sub-populations

“…In this work, we choose to use a CNA threshold of 2.2; this threshold is chosen based on some prior knowledge and some assumptions about the levels of EGFR and PDGFRA amplification that we expect to see in our tissue samples. Firstly, diploid cells that are not EGFR or PDGFRA gene amplified will have an associated CNA value equal to 2 [11,25], which applies to the healthy cells and non-amplified tumour cells in the tissue samples. Secondly, we assume that the EGFR and PDGFRA amplified cell sub-populations are homogeneous with respect to their gene copy numbers and, therefore, all cells in each of these subpopulations have the same CNA value associated to each of these genes, which we choose to equal 4; this corresponds to each of the alleles in an EGFR amplified cell containing an extra copy of the EGFR gene and similarly for the PDGFRA amplified population.…”

From single-molecule detection to next-generation sequencing: microfluidic droplets for high-throughput nucleic acid analysis

“…Hindson et al (2013) have compared ddPCR with qPCR in the microRNA quantification, with results indicating that ddPCR yields significantly greater precision and improved "day-to-day reproducibility" over qPCR. Such superior metrics suggest that ddPCR will continue to play an important role in molecular diagnostics of genetic diseases (Debrand et al 2015), cancers (Mehrian-Shai et al 2016;Watanabe et al 2015), infectious diseases (Bian et al 2015;Trypsteen et al 2016) and prenatal diagnosis (Orhant et al 2016). For example, epidermal growth factor receptor (EGFR) mutation is an important target for many cancer therapies, with the status of the EGFR mutation being closely related to the therapeutic effect of EGFR inhibitors, such as monoclonal antibodies and tyrosine kinase inhibitor (Lièvre et al 2006;Gazdar 2009).…”